arroyo
openvino_notebooks
arroyo | openvino_notebooks | |
---|---|---|
13 | 80 | |
3,326 | 1,991 | |
3.2% | 5.1% | |
9.6 | 9.9 | |
6 days ago | 7 days ago | |
Rust | Jupyter Notebook | |
Apache License 2.0 | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
arroyo
- FLaNK AI Weekly 18 March 2024
- Arryo 0.8 released — streaming SQL engine
-
Query Engines: Push vs. Pull
Interesting - I looked into your code a bit. I found your window aggregation library [1]. You may be interested in looking into the Rust implementation of some of the research work I've been a part of [2].
In Flink, I believe the reason they need to implement their own backpressure system is that they multiplex TCP connections. That is, they have multiple logical streams flowing through a single TCP connection. If that's the case, you need to do some work to 1) detect which logical stream is the one that's blocking, and 2) don't block because other logical streams may be able to use the active TCP connection.
Thinking it through, I think what Flink's approach buys is not necessarily better performance, but better just a manageable number of connections. That is, imagine you have a process P1 with operators A, B and C. And then P2 has D, E, F. Now imagine that this is a shuffle, where A, B and C are fully connected to D, E and F. In my old system, you would have 9 TCP connections. In Flink, you will have 1.
[1] https://github.com/ArroyoSystems/arroyo/blob/master/arroyo-w...
- Arroyo
- Show HN: Arroyo – Write SQL on streaming data
- Release v0.3.0 · ArroyoSystems/arroyo - Stream Processing Engine
- Arroyo 0.2 released - Rust stream processing engine, now on Kubernetes
- Distributed stream processing engine written in Rust
- ArroyoSystems/arroyo: Arroyo is a distributed stream processing engine written in Rust
- Arroyo, a new open-source SQL stream processing engine written in Rust
openvino_notebooks
- FLaNK-AIM Weekly 06 May 2024
- FLaNK AI Weekly 18 March 2024
- FLaNK Stack Weekly 19 Feb 2024
- FLaNK Stack Weekly 12 February 2024
- FLaNK Stack 05 Feb 2024
-
Optimum Intel OpenVino Performance
Also, credits for using zram in your VM setup; that's a smart hack for memory management. Have you tried tweaking other models like the ones in this OpenVINO notebook?
- FLaNK Stack Weekly 06 Nov 2023
- Trouvez-la plus vite
- Change your voice. FreeVC offers one-shot voice conversion, no text transcript required. Explore how OpenVINO powers AI solutions, see the code on GitHub.
- Vous aurez la banane
What are some alternatives?
bytewax - Python Stream Processing
chdb - chDB is an embedded OLAP SQL Engine 🚀 powered by ClickHouse
risingwave - SQL stream processing, analytics, and management. We decouple storage and compute to offer speedy bootstrapping, dynamic scaling, time-travel queries, and efficient joins.
deepeval - The LLM Evaluation Framework
Benthos - Fancy stream processing made operationally mundane
super-gradients - Easily train or fine-tune SOTA computer vision models with one open source training library. The home of Yolo-NAS.
cli - Railway CLI
starcoder - Home of StarCoder: fine-tuning & inference!
feldera - Feldera Continuous Analytics Platform
open_model_zoo - Pre-trained Deep Learning models and demos (high quality and extremely fast)
timely-dataflow - A modular implementation of timely dataflow in Rust
netron - Visualizer for neural network, deep learning and machine learning models